Hybrid vehicles, i.e., those that utilize both internal combustion and electric motors, provide drivers with dramatically increased fuel economy. Technologies such as engine start/stop, regenerative braking, battery conditioning, engine cylinder deactivation, transmission operation range and Interactive Decel Fuel Shut-Off (iDFSO) are used to limit fuel consumption and eliminate the need for on-board batteries to be recharged externally. Although drivers benefit greatly from the increased fuel economy, the driving experience can be affected by the operation of the hybrid powertrain. Particularly, hybrid powertrains tend to be programmed to operate in the most fuel conscious manner, which can leave the driver wanting more power from the vehicle, or feeling that the vehicle is not as responsive as they might prefer, especially on commonly-driven routes.
Generally, existing powertrains are unable to adapt to how a driver prefers a vehicle to operate along a particular route. Although known powertrain components such as those described in U.S. Pat. No. 4,982,620 can have limited integrated learning capacity, that learning capacity is confined to shift timing. Moreover, the learning capacity is not driver-controlled in any way, and it is driver and route agnostic. Yet, as noted above, the driver's perception of vehicle control can vary with hybrid powertrains because of the nature of how they operate. Accordingly, there is a need for a hybrid powertrain (and a powertrain generally) with an ability to learn how a driver prefers a vehicle operate on a given route and to subsequently optimize powertrain operation on that route according to the learned driving preferences.